Juggernaut XL V9+RDPhoto2 Lightning_4S

8851°

#fantasy #realistic #effects #backgrounds #vehicles #food

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Created by

KandooAI

on Civitai

Juggernaut XL 9 Lightning by KandooAI is a variant of the existing XL 9 model that can create images with lower guidance and steps, but is otherwise similar. Res: 832*1216 Sampler: DPM++ 2M Karras Steps: 30-40 CFG: 3-7 (less is a bit more realistic) Negative: Start with no negative, and add afterwards the Stuff you don´t wanna see in that image. I don´t recommend using my Negative Prompt, i simply use it because i am lazy :D VAE is already Baked In And a few keywords/tokens that I regularly use in training, which might help you achieve the optimal result from the version: Architecture Photography Wildlife Photography Car Photography Food Photography Interior Photography Landscape Photography Hyperdetailed Photography Cinematic Movie Still Mid Shot Photo Full Body Photo Skin Details And now, have fun trying it out

Creator notes

Updated the Prompting Guide For business inquires, commercial licensing, custom models, and consultation contact me under KandooAI@web.de Join Juggernaut now on Hey everyone, It’s been 8 months since the last version was released here on CivitAI. Of course, I haven’t been idle during that time . I completed several projects to ensure I’d have the financial means to keep exploring new architectures and possibly do full finetunes on them in the future. Juggernaut Flux (and its many sub-variants) was a ton of work, but ultimately, I’ve wrapped that chapter up. The training process gave me way too many headaches. To keep my sanity, I spent my spare time working on Juggernaut SDXL with the hope of maybe releasing one final version for you all. And that day has finally come. :) Juggernaut Ragnarok has improved in many areas: photorealism, digital painting, poses, hands, feet, and much more. That said, it’s still an SDXL model, and I don’t recommend comparing it to models like Flux, Reve, or Sora. For example, it still has limitations when it comes to text rendering or faces at a distance. I recommend using it as part of a pipeline for your projects. Example setup: / / → Juggernaut Ragnarok A quick personal note about Juggernaut: Honestly, I don’t know what comes next. After the release of Sora and similar tools, the open-source image generation space feels a bit dull in comparison. Nothing has really excited me enough to dive back into training (yes, I’m talking about HiDream too). So I’m seeing Juggernaut Ragnarok as a kind of farewell, especially since it’s unclear where things are headed with CivitAI in general. (You can download all Juggernaut versions from HuggingFace, by the way.) Last but not least: Have fun with the model, share your creations, and good luck with your projects! And in case you’re wondering: Yes, you can do anything you want with Juggernaut : merge it, train it, sell the image outputs, etc. Just a simple shoutout is all I ask. :) And now, here are the recommended settings: Recommended Settings(VAE is baked in): Res: 832*1216 (For Portrait, but any SDXL Res will work fine) Sampler: DPM++ 2M SDE Steps: 30-40 CFG: 3-6 (less is a bit more realistic) Negative: Start with no negative, and add afterwards the Stuff you don´t wanna see in that image. VAE is already Baked In HiRes: 4xNMKD-Siax_200k with 15 Steps and 0.3 Denoise + 1.5 Upscale And now, have fun trying it out. As always, I'm eagerly waiting for your pictures in the Gallery :) If you liked the model, please leave a Like. In the end, that's what helps me the most as a creator on CivitAI. :) Last but not least, I'd like to thank a few people without whom Juggernaut XL probably wouldn't have come to fruition: (Trained 3 Side Sets)

159,192 downloads · 3,961 likes on Civitai

SHA256

C8DF560D2992AC04299412BE6A36FA53A4E7A1B74F27B94867AD3F84F4B425A5

Juggernaut XL V9+RDPhoto2 Lightning_4S Popularity Trend

Heat score, last 12 months

Heat score

8,851°

This week

▼

0.6%

8,854° then, 8,851° now

This month

▼

2.4%

8,863° then, 8,851° now

Past year

▼

28.2%

8,996° then, 8,851° now

7,000°

Floor

The scale runs from 0° to 9,999°. Everything below 7,000° is kept for models no source reports on yet, which carry a stand-in number there so lists stay complete. 7,000° is where measured data begins: a model with real data but almost no downloads sits at the floor, and the measurements fill the degrees above it. The floor says nothing about the model; only the degrees above it do, and they are what separates one model from another.

+1,581°

Civitai downloads

159,192 downloads of this exact version on Civitai. Downloads are the heaviest ingredient and are counted on a log scale: ten times the downloads adds the same 300°, so a model with a million downloads is not a thousand times hotter than one with a thousand. The six download sources share that one term, split between them in proportion to their counts.

+540°

Likes

3,961 likes and thumbs up across the sources. A like weighs half a download, on the same log scale.

+77°

Adoption rate

About 10 downloads a day, measured between two readings of the sources, never guessed from a lifetime average. Speed weighs a quarter of the download term, so a fresh surge shows without letting a one-day spike outrank years of use.

+150°

Full model

+150° because this is a full model: a checkpoint, the weights themselves. A LoRA or an embedding is an add-on to someone else's weights and does not outrank a checkpoint of equal popularity.

−497°

Age

−497° because the SDXL weights came out in 2023. Every model inherits the age of the weights it is built on: 150° a year, up to 750°, and it keeps growing until then. Without it the top of the list would be 2022 and 2023 checkpoints on the strength of downloads that had years to pile up.

Show detailed breakdown

Every number on this site can be checked. This model's heat score is 8,851°, and here it is built one ingredient at a time, with the running total after each: the floor, the degrees each source adds, the bonus for the kind of model and what the age of its weights takes away. The colors are the bands of the chart above. The glossary at the end defines every term.

1
Start at the floor.
Why 7,000° and not zero: the scale runs from 0° to 9,999°, and the part below 7,000° is reserved for models no source reports on yet, which carry a stand-in number there so the lists stay complete and never outrank a model with data. 7,000° is where measured data begins. A model with real data but almost no downloads sits here; everything that follows is measurement, and the room above the floor holds ten tenfold steps in downloads at 300° each. The floor is the same for every model, so it decides nothing; the degrees above it do.
7,000°
running total
2
Add the downloads.
159,192 download-equivalents in all, from Civitai downloads. Ten times the downloads adds the same 300°, so size matters but never runs away with the score.
+1,581°
8,581°
running total
3
Add the likes.
3,961 likes and thumbs up, at half the weight of a download.
+540°
9,121°
running total
4
Add the adoption rate.
About 10 downloads a day right now, measured between two readings, at a quarter of the weight.
+77°
9,198°
running total
5
Bonus for a full model.
A checkpoint carries the weights themselves; add-ons do not outrank one of equal popularity.
+150°
9,348°
running total
6
Take off the age.
The SDXL weights came out in 2023: 150° a year, up to 750°, growing until then.
−497°
8,851°
running total
=
The heat score.
Where this model stands on every list of this site. Nothing else adjusts it.
8,851°

Glossary: the terms used here

Heat score: One number for how much a model is used and wanted right now, from 0° to 9,999°. Every list on this site that says hottest is sorted by it and nothing else.
Floor: The 7,000° every model with real data starts from. The scale runs from 0° to 9,999°; the part below the floor is reserved for stand-ins (models without data), so that a model with data always ranks above one without. The floor is the same for everyone and decides nothing; the degrees above it are the measurement.
Download-equivalents: Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
Log scale: Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
Likes: Thumbs up and likes from every source, worth half a download each on the log scale.
Adoption rate: How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
Measured and estimated: Measured means two readings of a source exist and the difference is real. Estimated means only today's total is known and the past is spread over the model's life; the site says which one it is showing.
Seeder: Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
AI Horde: A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
Generation sites: Sites that host their own copies of a model and let people generate with it, such as PixAI, SeaArt and Yodayo. Their downloads count like Civitai's and each generation run as one download.
OpenRouter tokens: A text model served through an API, such as Claude or GPT, has no weights to download, so its usage is measured in tokens: the pieces of text it read and wrote through OpenRouter, a gateway many apps use, over the last 30 days. Every 10,000,000 tokens count as one download. Source: OpenRouter (openrouter.ai/rankings), CC BY 4.0.
Full model (checkpoint): The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
LoRA and embedding: Small add-on files that steer someone else's weights toward a style, a character or a concept. They cannot run alone.
Family and weights: The base a model is built on, such as SD 1.5, SDXL, Flux or Wan. Every model inherits the release date of its family's weights.
Age: Degrees taken off for how long ago the family's weights came out: 150° a year, up to 750°. It keeps old downloads that had years to pile up from freezing the top of the list.
Family boost: A small, bounded nudge for LoRAs of a family this site is pushing forward right now, always listed in the breakdown.
Stand-in score: A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
New! (grace period): A model less than 7 days old shows New! instead of a score and holds no place in the rankings. Its score is computed from day one, but a model one day old grows faster than anything, so without the wait the week's #1 would always be whatever came out yesterday rather than what held up for a week.
Trend: How a model's growth over a period compares with the typical model's growth over the same period. Faster than typical reads as a rise, slower as a fall.
Typical model: The middle of the catalog: half the models with a figure grew faster over the period, half slower.

How this model's popularity has moved against the rest of the catalog: its growth in downloads, likes and usage over each period, measured against the typical model's growth over the same period, with its heat score at the time. Above the typical growth reads as a rise, below it as a fall. The past is reconstructed from today's totals, the model's first day and its measured download speed where two readings exist; a model that did not exist at the start of a period shows n/a.

Example renders

NSFW

Prompts and settings shared by the people who made these renders on Civitai. Pick a render to see how it was made.